From now on, Google Translate will rely more on AI (artificial intelligence) when it translates languages. Alphabet, the parent company, claims that its brand new Google Neural Machine Translation system will reduce errors by 80 percent compared to its current method.

Until today, Google has used what is called “phrase-based translation,” which is standard for the industry. With this method, a hand-coded algorithm breaks down a sentence into words or phrases and tries to match them a vast dictionary. The new system will use that same large dictionary to train two neural networks, one of which will deconstruct the original sentence to figure out what it means, while the other generates text in the output language.

Because AI algorithms don’t rely on human logic, they can often find better ways to do the job compared to the hand-coded algorithms, say the engineers. And as the network learns how to translate, no longer spending time dividing sentences into words or phrases, it discards the rules that humans thought were best and concentrates fully on the outcome. Such is the nature of AI. As Alan Turing wrote in 1950: “I believe that at the end of the century the use of words and general educated opinion will have altered so much that one will be able to speak of machines thinking without expecting to be contradicted.” (Computing machinery and intelligence). We’re getting there.

Google is releasing its new translation system for Mandarin Chinese first, and then adding new languages over coming months.